10 JUL 2026 - Back up to full speed! Let's be honest: for the last few months, TorrentFunk was painfully slow. Pages crawled, searches dragged, and just loading the site tested everyone's patience. We hunted the problem down to our network and rebuilt it from the ground up — smarter caching, a much bigger and faster connection, and a lot of fine-tuning under the hood. The difference is night and day: the site now loads in a fraction of a second. No more waiting around. Thanks for sticking with us through the slow spell. Now go discover your funk!
TITLE: MICROSOFT SQL SERVER 2012 WITH HADOOP
PUBLISHER: PACKT LANGUAGE: ENGLISH
LINK: http://is.gd/qKGY5w RELEASE TYPE: RETAIL
FORMAT: PDF RELEASE DATE: 2014.01.23
ISBN: 9781782177982 STORE DATE: 2013
SAVED.MONEY: 19 EURO DISKCOUNT: 01 x 05MB
AUTHOR: DEBARCHAN SARKAR
BOOK
With the explosion of data, the open source Apache Hadoop
ecosystem is gaining traction, thanks to its huge ecosystem that
has arisen around the core functionalities of its distributed
file system (HDFS) and Map Reduce. As of today, being able to
have SQL Server talking to Hadoop has become increasingly
important because the two are indeed complementary. While
petabytes of unstructured data can be stored in Hadoop taking
hours to be queried, terabytes of structured data can be stored
in SQL Server 2012 and queried in seconds. This leads to the need
to transfer and integrate data between Hadoop and SQL
Server
Microsoft SQL Server 2012 with Hadoop is aimed at SQL Server
developers. It will quickly show you how to get Hadoop activated
on SQL Server 2012 (it ships with this version). Once this is
done, the book will focus on how to manage big data with Hadoop
and use Hadoop Hive to query the data. It will also cover topics
such as using in-memory functions by SQL Server and using tools
for BI with big data
Microsoft SQL Server 2012 with Hadoop focuses on data integration
techniques between relational (SQL Server 2012) and
non-relational (Hadoop) worlds. It will walk you through
different tools for the bi-directional movement of data with
practical examples
You will learn to use open source connectors like SQOOP to import
and export data between SQL Server 2012 and Hadoop, and to work
with leading in-memory BI tools to create ETL solutions using the
Hive ODBC driver for developing your data movement projects
Finally, this book will give you a glimpse of the present day
self-service BI tools such as Excel and PowerView to consume
Hadoop data and provide powerful insights on the data